MACHINE-LEARNING BASED TUNING ALGORITHM FOR DUPLEXER SYSTEMS

Organization Name

Inventor(s)

MACHINE-LEARNING BASED TUNING ALGORITHM FOR DUPLEXER SYSTEMS - A simplified explanation of the abstract

This abstract first appeared for US patent application 18680493 titled 'MACHINE-LEARNING BASED TUNING ALGORITHM FOR DUPLEXER SYSTEMS

Abstract: This disclosure provides techniques for impedance matching. A radio frequency (RF) device includes a power detector to determine a transmitter leakage and a post-processing unit to determine a receiver leakage, and determines if isolation is acceptable based on the leakages. The RF device may include a device for measuring antenna impedance. Otherwise, the RF device may select multiple tuner settings (e.g., capacitor values) for test signals to be transmitted and received at a target frequency, determine multiple sets of leakage values, determine multiple reflection coefficients based on the multiple sets of leakage values, and determine an estimated antenna impedance at the target frequency based on the reflection coefficients. The RF device then determines impedance tuner settings based on the measured or estimated antenna impedance. Alternatively, the RF device determines impedance tuner settings using an inverse machine-learning model based on a determined matching impedance.

Key Features and Innovation:

Techniques for impedance matching in RF devices.
Utilization of power detector and post-processing unit to determine leakage and isolation.
Measurement of antenna impedance and selection of tuner settings for test signals.
Calculation of reflection coefficients to estimate antenna impedance.
Use of machine-learning model for determining impedance tuner settings.

Potential Applications:

Wireless communication systems.
Antenna design and optimization.
RF testing and calibration equipment.
IoT devices and sensors.
Satellite communication systems.

Problems Solved:

Ensuring proper impedance matching in RF devices.
Improving signal quality and efficiency.
Enhancing overall performance of wireless systems.
Simplifying antenna impedance measurement and tuning processes.
Facilitating accurate calibration of RF equipment.

Benefits:

Enhanced signal transmission and reception.
Optimal performance of RF devices.
Reduced interference and signal loss.
Streamlined antenna impedance tuning.
Improved reliability and accuracy in wireless communication.

Commercial Applications: Impedance matching techniques in RF devices for improved signal quality and performance in wireless communication systems.

Questions about Impedance Matching: 1. How does impedance matching impact the efficiency of RF devices? Impedance matching ensures maximum power transfer between components, leading to improved signal quality and efficiency in RF devices.

2. What role does antenna impedance play in the performance of wireless communication systems? Antenna impedance affects the matching between the transmitter, receiver, and the antenna, influencing signal transmission and reception quality.

Original Abstract Submitted

This disclosure provides techniques for impedance matching. A radio frequency (RF) device includes a power detector to determine a transmitter leakage and a post-processing unit to determine a receiver leakage, and determines if isolation is acceptable based on the leakages. The RF device may include a device for measuring antenna impedance. Otherwise, the RF device may select multiple tuner settings (e.g., capacitor values) for test signals to be transmitted and received at a target frequency, determine multiple sets of leakage values, determine multiple reflection coefficients based on the multiple sets of leakage values, and determine an estimated antenna impedance at the target frequency based on the reflection coefficients. The RF device then determines impedance tuner settings based on the measured or estimated antenna impedance. Alternatively, the RF device determines impedance tuner settings using an inverse machine-learning model based on a determined matching impedance.